This invention relates generally to inspection of rotating machinery components, and more particularly, to methods and systems for optical inspection of rotating machinery components.
At least some known large machines achieve an optimal efficiency of operation when the machine is maintained operating on-line. For example, gas and steam turbines for electrical power generation are very expensive and are often not removed from service for inspection or maintenance unless absolutely necessary. However, components within the machine typically can only be inspected while the machine is offline and in some cases at least partially disassembled. Known conventional methods of inspecting for example, turbine blades such as surface inspection methods (i.e., magnetic particle testing; eddy current testing; dye penetrant techniques) and volumetric methods (i.e., ultrasonic testing) rely on the periodic disassembly of the turbine. Disassembling a turbine to inspect it is an expensive process and takes the turbine out of service for a significant amount of time.
Because none of the foregoing techniques are suitable for inspection while the turbine is on-line and running under load, other turbine inspection techniques are used in an attempt to monitor machine components during full load operation. For example, vibration analysis, acoustic emissions (AE), passive proximity probes, and ultrasound or eddy current techniques have been employed. Each of these inspection methods has its own unique set of disadvantages. The interior environment of a turbine is hostile for electrical sensing equipment. For example, a gas turbine typically operates at an internal temperature of about 1200 degrees Celsius (2192 degrees Fahrenheit) and a steam turbine may have temperatures of approximately 550 degrees Celsius (1022 degrees Fahrenheit). High pressures and reactive chemistry within turbines provide further detriment to inspection and measurement equipment.
Reliable and early detection of wear and/or failures of the components would permit advantageous scheduling of an outage for repair. Additionally, knowledge of the condition of such components may permit an engineering evaluation that extends the time between outages further facilitates improving the efficiency of the machine.